APPLIED STATISTICS AND DATA SCIENCE CURRICULUM
Curriculum
To obtain a master's degree in Applied Statistics and Data Science, students must complete 10 three-credit courses, six of which are required courses and four of which are elective courses. Students can choose to tailor their degree by completing an Applied Statistics, Biostatistics, or Data Science track. Each track consists of a particular set of required courses together with two of four electives chosen from a particular subset of electives, as shown in the track subsection below.
Required Courses
For all tracks, students are required to take the following four courses:
- STAT 7404 - Statistical Methods
- STAT 7500 - Statistical Programming
- STAT 8400 - Statistical Theory I
- STAT 8406 - Regression Methods
Students completing the Applied Statistics or Biostatistics tracks must additionally take the following two courses:
- STAT 8401 - Statistical Theory II
- STAT 8412 - Linear Models
Students completing the Data Science track must complete the following:
- STAT 8480 - Data Mining and Predictive Analytics
- STAT 8401 - Statistical Theory II or STAT 8412 - Linear Models
Elective Courses
The four elective courses can be chosen from the list below. Most elective courses are offered by the program every two-to-three years.
- STAT 8401 - Statistical Theory II (for Data Science track)
- STAT 8408 - Multivariate Methods
- STAT 8410 - Bayesian Statistics
- STAT 8412 - Linear Models (for Data Science track)
- STAT 8414 - Categorical Data Analysis
- STAT 8416 - Design of Experiments
- STAT 8444 - Time Series and Forecasting
- STAT 8446 - Survival Data Analysis
- STAT 8448 - Clinical Trials
- STAT 8450 - Longitudinal Data Analysis
- STAT 8452 - Nonparametric Statistics
- STAT 8454 - Sampling Methods
- STAT 8462 - Stochastic Modeling
- STAT 8470 - Statistical Genetics
- STAT 8480 - Data Mining & Predictive Analytics (for Applied Statistics/Biostatistics track)
- STAT 8490 - Deep Learning
- STAT 8790 - Selected Topics I
- STAT 8795 - Selected Topics II
- STAT 8800 - Independent Study
With permission from the Graduate Director, certain courses from the Mathematics or Computer Science graduate programs may count as an elective, including, MAT 8430 - Operations Research, CSC 8490 - Database Systems, and CSC 8515 - Machine Learning.
Degree Tracks
These tracks are meant to guide students who are interested in specific specialties within the field of Statistics and Data Science. While these tracks are not listed on transcripts, students are encouraged to list their track on their resume/CV. Note that a track is not required in order to receive a Master’s degree in Applied Statistics and Data Science.
Applied Statistics |
Biostatistics |
Data Science |
|
Required Courses |
1. Stat Methods |
1. Stat Methods |
1. Stat Methods |
Elective Courses (at least two of these) |
Nonparametric Statistics |
Clinical Trials |
Deep Learning |
Other Electives |
Two electives from any track |
Two electives from any track |
Two electives from any track |
Some of the electives listed above could be placed in multiple tracks (e.g. Nonparametric, Bayesian, and Sampling could be useful for Biostatisticians, Categorical Data Analysis and Design of Experiments could be useful for all types of Statisticians and Data Scientists, Multivariate could be especially useful for Data Scientists, etc.). However, by taking two of the courses listed within the track, you will have completed courses more integral to those track areas.
Other Details
Course Scheduling
During the academic year, classes are typically held one night a week, Monday through Thursday, from 6:15 p.m. to 8:45 p.m. Times may vary during the summer.
While full-time students can finish their coursework in 1.5 to 2 years, students are welcome to attend part-time as long as the degree is completed within six years of starting.
Students in the Master of Science in Applied Statistics and Data Science program must complete Statistical Methods, Regression Methods and Statistical Theory I within their first 15 credits. Students should consult with the Director of the Applied Statistics and Data Science Graduate Program to formulate a program of study suitable to their individual needs.
Comprehensive Exam
After completing at least 21 credits in the program but before graduation, students must pass a Comprehensive Exam. The exam covers material from three of the core required courses: Statistical Methods, Regression Methods, and Statistical Programming. The purpose of the exam is ensure that students have a strong foundation in statistical analysis and data wrangling and also to ensure that the MS in Applied Statistics and Data Science degree remains highly valued.
The Comprehensive exam is given twice a year - once in the fall semester, usually in November, and once in the spring semester, usually in April. The 3.5 hour exam is usually given on a Saturday morning starting at 9 a.m. Current students can find more details and copies of previous exams on the .
Ready for the Next Step?
DEADLINES
March 1: For Fall admission with funding consideration
May 1: For Fall admission for international students without funding
August 1: For admission without funding for the fall
October 15: For Spring admission for international students without funding
December 1: For admission without funding for the spring
ALUMNI NEWS
A New Treatment for COVID-19 Approved for Emergency Use. This Applied Statistics Alum Is on the Team That Helped Make It Happen
Duane Stanton '19 MS, a statistical modeling expert with GlaxoSmithKline and a graduate of the ÄÌÌÇÖ±²¥ master’s program in Applied Statistics, assisted in preparing a new monoclonal antibody treatment for market.